{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**复习：**回顾学习完第一章，我们对泰坦尼克号数据有了基本的了解，也学到了一些基本的统计方法，第二章中我们学习了数据的清理和重构，使得数据更加的易于理解；今天我们要学习的是第二章第三节：**数据可视化**，主要给大家介绍一下Python数据可视化库Matplotlib，在本章学习中，你也许会觉得数据很有趣。在打比赛的过程中，数据可视化可以让我们更好的看到每一个关键步骤的结果如何，可以用来优化方案，是一个很有用的技巧。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2 第二章：数据可视化"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 开始之前，导入numpy、pandas以及matplotlib包和数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 加载所需的库\n",
    "# 如果出现 ModuleNotFoundError: No module named 'xxxx'\n",
    "# 你只需要在终端/cmd下 pip install xxxx 即可\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  PassengerId  Survived  Pclass  \\\n",
       "0           0            1         0       3   \n",
       "1           1            2         1       1   \n",
       "2           2            3         1       3   \n",
       "3           3            4         1       1   \n",
       "4           4            5         0       3   \n",
       "\n",
       "                                                Name     Sex   Age  SibSp  \\\n",
       "0                            Braund, Mr. Owen Harris    male  22.0    1.0   \n",
       "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0    1.0   \n",
       "2                             Heikkinen, Miss. Laina  female  26.0    0.0   \n",
       "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0    1.0   \n",
       "4                           Allen, Mr. William Henry    male  35.0    0.0   \n",
       "\n",
       "   Parch            Ticket     Fare Cabin Embarked  \n",
       "0    0.0         A/5 21171   7.2500   NaN        S  \n",
       "1    0.0          PC 17599  71.2833   C85        C  \n",
       "2    0.0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3    0.0            113803  53.1000  C123        S  \n",
       "4    0.0            373450   8.0500   NaN        S  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#加载result.csv这个数据\n",
    "text = pd.read_csv(r'result.csv')\n",
    "text.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.7 如何让人一眼看懂你的数据？\n",
    "《Python for Data Analysis》第九章"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.7.1 任务一：跟着书本第九章，了解matplotlib，自己创建一个数据项，对其进行基本可视化"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "【思考】最基本的可视化图案有哪些？分别适用于那些场景？（比如折线图适合可视化某个属性值随时间变化的走势）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#思考回答\n",
    "#这一部分需要了解可视化图案的的逻辑，知道什么样的图案可以表达什么样的信号b\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.7.2 任务二：可视化展示泰坦尼克号数据集中男女中生存人数分布情况（用柱状图试试）。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#代码编写\n",
    "sex=text.groupby('Sex')['Survived'].sum()\n",
    "sex.plot.bar()\n",
    "plt.title('survived_count')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "891"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "text['Survived'].count()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "【思考】计算出泰坦尼克号数据集中男女中死亡人数，并可视化展示？如何和男女生存人数可视化柱状图结合到一起？看到你的数据可视化，说说你的第一感受（比如：你一眼看出男生存活人数更多，那么性别可能会影响存活率）。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'count')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#思考题回答\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.7.3 任务三：可视化展示泰坦尼克号数据集中男女中生存人与死亡人数的比例图（用柱状图试试）。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'count')"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#代码编写\n",
    "# 提示：计算男女中死亡人数 1表示生存，0表示死亡\n",
    "text.groupby(['Sex','Survived'])['Survived'].count().unstack().plot(kind='bar',stacked='True')\n",
    "plt.title('survived_count')\n",
    "plt.ylabel('count')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "【提示】男女这两个数据轴，存活和死亡人数按比例用柱状图表示"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.7.4 任务四：可视化展示泰坦尼克号数据集中不同票价的人生存和死亡人数分布情况。（用折线图试试）（横轴是不同票价，纵轴是存活人数）"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "【提示】对于这种统计性质的且用折线表示的数据，你可以考虑将数据排序或者不排序来分别表示。看看你能发现什么？"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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boFIp0xiTyAEAQASSG6DMNE4PFAAAiEBiA1Ta6IECAADRSGyASqVMzkmOEAUAAEKW2ACVNpPERHIAABC+5AYo/5UxjAcAAMKW2ACVSnk9UOPjMTcEAAAkTmID1MQQHj1QAAAgZMkNUIUeKAIUAAAIWWIDVMoKQ3gEKAAAEK7EBqhCDxSfwgMAAGFLbIAqTCJnDhQAAAhbYgNU2vgUHgAAiEZyAxTrQAEAgIgkNkAxiRwAAEQlsQGKSeQAACAqiQ1QWX8Mb2SMSVAAACBciQ1QTRnvpR0YJUABAIBwJTdAZdOSpAOjYzG3BAAAJE1iA1RzoQdqhB4oAAAQrsQGqIM9UAQoAAAQruQGqIk5UAzhAQCAcCU+QA0zhAcAAEKW3ADFJHIAABCRxAaoZpYxAAAAEakYoMwsb2Y/NbNNZrbRzK71H19jZq+Y2Xr/68PRN7d6Ez1QDOEBAICQZarYZlTSnznnnjCzeZIGzOwB/7kbnXNfia55tWMSOQAAiErFAOWc2yppq397n5ltknRU1A2brkzKlDImkQMAgPCZc9VfbNfMuiQ9LOlESf9Z0lWS3pC0Tl4v1e4S+6yWtFqSOjo6Vvb19U270VMZGhpSW1ubJOmaB/arN5/Rpe9uivSc9a64ZqgONasNdQuOmgVHzYKjZqX19vYOOOe6Sz1XdYAyszZJD0n6knPu+2bWIWmnJCfpi5KWOueunuoY3d3dbt26dYEaH1R/f796enokSadef79+/5Rluv7CEyM9Z70rrhmqQ81qQ92Co2bBUbPgqFlpZlY2QFX1KTwzy0r6nqTbnXPflyTn3Dbn3JhzblzSNySdHlaDw9KUSTOJHAAAhK6aT+GZpFskbXLO3VD0+NKizS6StCH85k1PUzbFJHIAABC6aj6Fd6akyyU9bWbr/cf+UtJlZrZC3hDeZknXRNC+aWnKpJhEDgAAQlfNp/AekWQlnvph+M0JV3M2TQ8UAAAIXWJXIpe8HihWIgcAAGFLeIBKE6AAAEDoEh6gmEQOAADCl+wAlWUSOQAACF+iA1RzhknkAAAgfIkOUE3ZFAtpAgCA0CU7QDGJHAAARCDhAYpJ5AAAIHzJDlDZtIZHxlXtBZMBAACqkewAlfFe3ttjDOMBAIDwNESAYh4UAAAIU7IDVDYtSXwSDwAAhCrZAWqiB4qJ5AAAIDyJDlDNhR4ohvAAAECIEh2gCj1QwyP0QAEAgPA0RICiBwoAAIQp4QGKSeQAACB8yQ5QWSaRAwCA8CU6QDVnmEQOAADCl+gAVeiBYhI5AAAIU7IDFJPIAQBABBIeoBjCAwAA4Ut0gGouTCJnCA8AAIQo0QGKHigAABCFRAeobNpkRg8UAAAIV6IDlJmpKZOiBwoAAIQq0QFK8obxCFAAACBMiQ9QzdkUK5EDAIBQJT5ANWXSXAsPAACEqgECVErD9EABAIAQJT5Azcmk9DZzoAAAQIgSH6Cy6ZRGxlzczQAAAAnSAAHKNDJGDxQAAAhPAwSolEbpgQIAACFKfIDKpFN6mx4oAAAQosQHqGzKNDpOgAIAAOFJfoBKpzQyyhAeAAAIT+IDVCZtGqEHCgAAhCjxAWpOOsWn8AAAQKgSH6AyaeNTeAAAIFSJD1BZeqAAAEDIGiRA0QMFAADC0wABipXIAQBAuBIfoDKsRA4AAEKW+ACV9Vcid44QBQAAwpH8AJUySdLYOAEKAACEI/kBKuO9RCaSAwCAsCQ+QGX8HihWIwcAAGFJfIDKpr2XyERyAAAQloYJUCxlAAAAwpL4AJVJ+0N4BCgAABCSigHKzPJm9lMz22RmG83sWv/xdjN7wMye9//NRd/c4OakmUQOAADCVU0P1KikP3POvUfS+yX9RzM7XtLnJD3onDtW0oP+/Vmn0AM1Sg8UAAAIScUA5Zzb6px7wr+9T9ImSUdJulDSbf5mt0n6aERtnJbCHKi3CVAAACAkFmSFbjPrkvSwpBMl/cY5t7Doud3OucOG8cxstaTVktTR0bGyr69vmk2e2tDQkNra2ibur98+qr974oD+6xnNeueCdKTnrleTa4bKqFltqFtw1Cw4ahYcNSutt7d3wDnXXeq5TLUHMbM2Sd+T9J+cc2+YWVX7OedulnSzJHV3d7uenp5qT1mT/v5+FZ8j/fwO6YnHdfIpp6q7qz3Sc9eryTVDZdSsNtQtOGoWHDULjpoFV9Wn8MwsKy883e6c+77/8DYzW+o/v1TS9miaOD2ZFJPIAQBAuKr5FJ5JukXSJufcDUVP3SPpSv/2lZLuDr950zcnwzIGAAAgXNUM4Z0p6XJJT5vZev+xv5T0ZUl3mtknJP1G0iWRtHCaCj1Qo1zKBQAAhKRigHLOPSKp3ISnD4bbnPBNfApvlCE8AAAQjsSvRJ4trANFDxQAAAhJAwQoroUHAADClfgAdfBaeAzhAQCAcCQ+QNEDBQAAwtYwAWqUHigAABCSxAeog0N49EABAIBwJD5AzUmzEjkAAAhX4gNUJkUPFAAACFfiA1Q6ZTKTRglQAAAgJIkPUGambCqlkXGG8AAAQDgSH6AkbzXykVF6oAAAQDgaIkBl0imN0gMFAABC0hABKptO6W3mQAEAgJA0SIAyJpEDAIDQNEiASrEOFAAACE1DBKhM2lgHCgAAhKYhAlQ2lSJAAQCA0DRGgMoYFxMGAAChaYgAlUnxKTwAABCehghQc9IpeqAAAEBoGiJAMYkcAACEqSECVDbNtfAAAEB4GiRAcS08AAAQngYJUCmNjhOgAABAOBoiQGVYiRwAAISoIQJUlknkAAAgRI0RoFiJHAAAhKgxAhQrkQMAgBA1RIBiJXIAABCmhghQ2TQ9UAAAIDwNEqBYxgAAAISnIQJUYRkD5+iFAgAA09cQAWpO2iRJo1zOBQAAhKAhAlQm7b1MljIAAABhaIgAlZ0IUPRAAQCA6WuQAOUN4dEDBQAAwtAgAcp7mSxlAAAAwtAQASqTogcKAACEpyEC1JwMk8gBAEB4GiJAZVJMIgcAAOFpiADFJHIAABCmBglQ3su8/bGX9fhLu2JuDQAAqHcNEaDy7a1qyab1nce36LofbIy7OQAAoM41RIA65og2PXP9ebrijKP1m11vxt0cAABQ5xoiQEmSmSmfa9W+4VHtfXMk7uYAAIA61jABSpLy7S2SpC276YUCAAC1a6gA1ZlrlSRtYRgPAABMQ0MFqHy7H6DogQIAANPQUAFqQUtW85oz2rLrrbibAgAA6lhDBShJyuda6YECAADT0ngBqr1Fg7vpgQIAALWrGKDM7Jtmtt3MNhQ9tsbMXjGz9f7Xh6NtZnjyuVYN7n5TznFdPAAAUJtqeqBulXR+icdvdM6t8L9+GG6zopNvb9XwyLh2DB2IuykAAKBOVQxQzrmHJSXmAnKFtaD+509e0CPP74y5NQAAoB5ZNUNZZtYl6V7n3In+/TWSrpL0hqR1kv7MObe7zL6rJa2WpI6OjpV9fX1htLusoaEhtbW1lX1+1/C4/vLf39LwmNTebLqhpzXS9tSDSjXD4ahZbahbcNQsOGoWHDUrrbe3d8A5113quVoDVIeknZKcpC9KWuqcu7rScbq7u926desCND24/v5+9fT0TLnN2LjTV//tOf39T17Qr/7b+WrKpCNt02xXTc1wKGpWG+oWHDULjpoFR81KM7OyAaqmT+E557Y558acc+OSviHp9Ok0cKalU6ajF82VJL3CJ/IAAEBANQUoM1tadPciSRvKbTtbdeYK18UjQAEAgGAylTYws+9I6pG02MwGJX1BUo+ZrZA3hLdZ0jXRNTEaE5d14bp4AAAgoIoByjl3WYmHb4mgLTOqY36zsmljVXIAABBYw61EXpBOmY5ayKrkAAAguIYNUJI3jDfIEB4AAAiooQNUZ66VSeQAACCwhg5Q+fYW7dr/tvYfGI27KQAAoI40dIDqzPmfxGMiOQAACKChA1S+sBbULobxAABA9Ro7QPlrQQ3SAwUAAAJo6AC1aO4ctWTT9EABAIBAGjpAmZny7S3MgQIAAIE0dICSpHyulcu5AACAQBo+QHXmvNXInXNxNwUAANSJhg9Q+fZWDR0Y1d63RuJuCgAAqBMNH6Am1oJiIjkAAKhSwweofLu/FhQTyQEAQJUIUO2FHigCFAAAqE7DB6j5zVktaMnSAwUAAKrW8AFK8obxBnczBwoAAFSHACWpcyFrQQEAgOoRoHSwB4q1oAAAQDUIUPImkh8YHdeOfQfibgoAAKgDBCh5l3ORWMoAAABUhwClorWgWEwTAABUgQClg6uRD9IDBQAAqkCAktScTWtxWxM9UAAAoCoEKF++vYU5UAAAoCoEKF8+10qAAgAAVSFA+fLtLXp1z7BGx8bjbgoAAJjlCFC+fK5VY+NOr70xHHdTAADALEeA8uXb/bWgmEgOAAAqyMTdgNmisJjm954Y1Avb90lm+tB7OnTkguaYWwYAAGYbApRv6cJmLW6bo38eGNQ/DwxKkp57bZ+++NETY24ZAACYbQhQvmw6pUc+e7aGDoxKkq785uN6eRefygMAAIcjQBVpzqbVnE1LkroWzdWmrW/E3CIAADAbMYm8jM5ciwZ3v6XxcRd3UwAAwCxDgCqjs71Vb4+Na/u+A3E3BQAAzDIEqDLyuRZJYnVyAABwGAJUGQfXhSJAAQCAQxGgyjhqodcDNbibhTUBAMChCFBlNGfT6pjfRA8UAAA4DAFqCp25VuZAAQCAwxCgppDPtXBtPAAAcBgC1BTy7a3auvctjYyNx90UAAAwixCgppDPtWrcSVv3DMfdFAAAMIsQoKbQ2V74JB7zoAAAwEEEqCnkc/5aUAQoAABQhAA1haULmpVOGRPJAQDAIQhQU8ikU1q6oJkeKAAAcAgCVAX5XCuLaQIAgEMQoCrIt7doC5dzAQAARQhQFeRzrdqx74CGR8bibgoAAJglCFAV5Nu9T+JxUWEAAFBQMUCZ2TfNbLuZbSh6rN3MHjCz5/1/c9E2Mz6dOW8tKCaSAwCAgmp6oG6VdP6kxz4n6UHn3LGSHvTvJ9JEDxQTyQEAgK9igHLOPSxp16SHL5R0m3/7NkkfDbdZs8eStibNyaTU/6sd+vGG1+Sci7tJAAAgZlZNIDCzLkn3OudO9O/vcc4tLHp+t3Ou5DCema2WtFqSOjo6Vvb19YXQ7PKGhobU1tYW6jGvX/uWXtzrXVB4zRnN6lqQDvX4cYuiZklHzWpD3YKjZsFRs+CoWWm9vb0DzrnuUs9loj65c+5mSTdLUnd3t+vp6Yn0fP39/Qr7HO8/c0y/2LxLl9/yuBZ1vUc9pywL9fhxi6JmSUfNakPdgqNmwVGz4KhZcLV+Cm+bmS2VJP/f7eE1afZpzqb13nd4HWxMJgcAALUGqHskXenfvlLS3eE0Z/aa25RR+9w5XBcPAABUtYzBdyStlfRbZjZoZp+Q9GVJHzKz5yV9yL+fePlciwbpgQIAoOFVnAPlnLuszFMfDLkts15ne6s2vrI37mYAAICYsRJ5AJ25Fr2y5y2NjbOUAQAAjYwAFUA+16qRMaft+4bjbgoAAIgRASqAwqrkTCQHAKCxEaACyBeui8dlXQAAaGgEqACOyrXIjLWgAABodASoAJoyaXXMa9ZjL+7SfRtfYzI5AAANigAV0LuXztPaF1/XNd8e0CMv7Iy7OQAAIAYEqIC+9scr9f1P/bYkafPO/TG3BgAAxIEAFVBzNq1T8wvVnE0xmRwAgAZFgKqBmakz18pkcgAAGhQBqkb5XAvrQQEA0KAIUDXKt9MDBQBAoyJA1Sifa9W+4VHtfWsk7qYAAIAZRoCqUb6dVckBAGhUBKgadea86+INMowHAEDDIUDVKJ/jwsIAADQqAlSNFrRmNa85w0RyAAAaEAFqGvK5Vj25ZY8eeGab3h4dj7s5AABghhCgpuHdR87Tk4N79R++tU4/fHpr3M0BAAAzhAA1DX/9ByfpR9eepZRJL3JdPAAAGgYBahqaMmm9Z+l8HTm/WYMsZwAAQMMgQIWgk1XJAQBoKASoEHTmWjS4m+UMAABoFASoEORzrXrtjWEdGB2LuykAAGAGEKBCkG9vlXPSq3uG424KAACYAQSoEORzXBcPAIBGQoAKQb7dv6wLE8kBAGgIBKgQdMxvVjZtXBcPAIAGQYAKQTplWrawhR4oAAAaRCbuBiRFPteqTVvf0H0bX5tyu1zrHJ2+vH2GWgUAAKJAgArJbx05T4+8sFPXfHug4rY//fMeLV88dwZaBQAAokCACslnz3+3/uC9nXJyZbd5bts+/ekdT+qlnUMEKAAA6hgBKiRzMikdv2z+lNssmdckSUw2BwCgzjGJfAYtaWtSczbFelEAANQ5AtQMMjN15rjwMAAA9Y4ANcPyuRaG8AAAqHMEqBlGDxQAAPWPADXD8u0t2jc8qr1vjcTdFAAAUCMC1AzL5/zr5jGRHACAukWAmmGFCw8PMowHAEDdIkDNsIM9UEwkBwCgXrGQ5gyb35LRvKaMHntpl951xMHVyJsyab3/nYuUTlmMrQMAANUgQM0wM9NxR87Tv23apn/btO2Q575xRbc+dHxHTC0DAADVIkDF4JYru/Xy6wfnQA2PjGnVzT/XizuGJBGgAACY7QhQMVjYOkcLW+dMeizL+lAAANQJJpHPEp2sUA4AQN0gQM0SeVYoBwCgbhCgZol8e6te2f2WnHNxNwUAAFRAgJol8rkWHRgd1459B+JuCgAAqIAANUt0+iuUM4wHAMDsR4CaJfK5FkmsUA4AQD2Y1jIGZrZZ0j5JY5JGnXPdYTSqEXVykWEAAOpGGOtA9TrndoZwnIbWnE1rybwmhvAAAKgDLKQ5i+RzLXpm6xv69+d3TLld+9w5OmHZghlqFQAAmMym87F5M3tJ0m5JTtLXnXM3l9hmtaTVktTR0bGyr6+v5vNVY2hoSG1tbZGeIyrf3HBADw+OVtzOJN3Q06JcczhT2Oq5ZnGhZrWhbsFRs+CoWXDUrLTe3t6BctOTphugljnnXjWzIyQ9IOkzzrmHy23f3d3t1q1bV/P5qtHf36+enp5IzxGV/QdGtWnrG1Nus/HVN/SFezbqO//h/TrjXYtCOW891ywu1Kw21C04ahYcNQuOmpVmZmUD1LSG8Jxzr/r/bjezuySdLqlsgMLU5jZl1N3VPuU2S+Y1SZIGd78pKZwABQAAgql5DMjM5prZvMJtSedK2hBWw1Da0gUtSpm0ZTfLHQAAEJfp9EB1SLrLzArH+f+dcz8OpVUoa04mpSPnN2uQ5Q4AAIhNzQHKOfeipFNCbAuq1NnOhYcBAIgTK5HXoXyulRXLAQCIEQGqDuXbW7Rt37AOjI7F3RQAABoSAaoO5XOtck56dc9w3E0BAKAhEaDqUL6d6+YBABAnAlQd6sy1SBITyQEAiAnXwqtDHfOblU2b1m3erXcunv7S+5teH1PTr18/7PGmbEorOhcqlbJpnwMAgCQhQNWhdMr0riVtuuuXr+iuX74SzkF/8fOSD99yZbc++J6OcM4BAEBCEKDq1K0fP10v7dwfyrHWr1+vFStWHPLYgdExXfWPv9AL24cIUAAATEKAqlNHLmjWkQuaQznWgS3pkhcmXtCSZZ4VAAAlMIkcZeXbW1iwEwCAEghQKCuf45IxAACUQoBCWfn2Vg3ufkvj4y7upgAAMKsQoFBWZ65Fb4+Oa8fQgbibAgDArEKAQln5nLfi+SDDeAAAHIIAhbLy7f6K50wkBwDgEAQolNWZ45p7AACUQoBCWc3ZtJbMa+KTeAAATMJCmphSZ65Fz762T+s274q7KVNKpUwnLlugORn+JgAARI8AhSkds6RN3x0Y1MVfWxt3Uyr67Pnv1id73hV3MwAADYAAhSn91UeO1wUrlsXdjIr+9I4n9fz2fXE3AwDQIAhQmNKClqzOOnZJ3M2oaPniVg3yaUEAwAxhwggSgcvOAABmEgEKidDZ3qrX3hjWgdGxuJsCAGgABCgkQj7XIuekrXuG424KAKABEKCQCPl2f9FPhvEAADOAAIVEmAhQTCQHAMwAAhQS4cj5zcqkjB4oAMCMIEAhEdIp07KFLVy3DwAwIwhQSIx8e4sGdzOEBwCIHgtpIjHyuVbd/8w2PbllT+TnenHvmHIzcJ6kmVy3jvnNOnJBc3wNAoAaEaCQGO9a0qZd+7fowpt+NjMnXDtD50maorotbM3ql5//kMwsxgYBQHAEKCTG5WccreOOnKex8fHIz/XUU0/r5JNPivw8SVNct4d+tUO3rX1ZO/Yd0BHz6YUCUF8IUEiM5mxaHzhuZq7bl3ptk3re3TEj50qS4rqZTLetfVlbdr9JgAJQd5hEDiAW+fYWSWLiP4C6RIACEIujFhYWP2XpCQD1hwAFIBYtc9Ja3NbE6vEA6hIBCkBs8u0trB4PoC4RoADEJp9rJUABqEsEKACxybe36NU9wxodi37pCQAIEwEKQGw6c60aG3faunc47qYAQCAEKACxyef8T+IxjAegzrCQJoDYFNaCWrd5txa0ZGNuzez08htj2vjq3ribUVeoWXD1WLPOha1a0Brf+wYBCkBsli1sUVMmpRseeE43PPBc3M2ZvR59JO4W1B9qFlyd1ex//uGp+sjJy2I7PwEKQGyy6ZS+/6nfZjXyKWzYsEEnnnhi3M2oK9QsuHqs2SmdC2M9PwEKQKxOWLZAJyxbEHczZq2mHc+q54Qj425GXaFmwVGz4JhEDgAAEBABCgAAICACFAAAQEAEKAAAgIAIUAAAAAERoAAAAAKaVoAys/PN7Fdm9oKZfS6sRgEAAMxmNQcoM0tLuknS70k6XtJlZnZ8WA0DAACYrabTA3W6pBeccy86596W1CfpwnCaBQAAMHtNJ0AdJWlL0f1B/zEAAIBEM+dcbTuaXSLpPOfc/+Hfv1zS6c65z0zabrWk1ZLU0dGxsq+vb3otrmBoaEhtbW2RniNpqFlw1Kw21C04ahYcNQuOmpXW29s74JzrLvXcdK6FNygpX3S/U9Krkzdyzt0s6WZJ6u7udj09PdM4ZWX9/f2K+hxJQ82Co2a1oW7BUbPgqFlw1Cy46Qzh/ULSsWa23MzmSLpU0j3hNAsAAGD2qrkHyjk3amaflnSfpLSkbzrnNobWMgAAgFlqOkN4cs79UNIPQ2oLAABAXWAlcgAAgIAIUAAAAAERoAAAAAIiQAEAAAREgAIAAAio5pXIazqZ2Q5JL0d8msWSdkZ8jqShZsFRs9pQt+CoWXDULDhqVtrRzrklpZ6Y0QA1E8xsXbll11EaNQuOmtWGugVHzYKjZsFRs+AYwgMAAAiIAAUAABBQEgPUzXE3oA5Rs+CoWW2oW3DULDhqFhw1Cyhxc6AAAACilsQeKAAAgEgRoAAAAAKKPUCZWYuZPWRmaf/+35jZRjPbZGZ/b2ZWYp8mM7vDzF4ws8fMrKvouTEzW+9/3VPF+Usey8yWmNmPw3ul4SmumZmtMLO1fs2eMrNVRdvdYmZP+o//s5m1lTnelWb2vP91ZRXn/10ze8LMRs3s4qLHZ1XNAtTJzOxLZvac/333JyWONdX+t5rZS0XfdyuqaFvJmptZn5kdG8LLn3y+yT9nPzazPWZ276TtSr4WM7vQf93rzWydmf1OhfP9DzMbmvRYj7//RjN7yH8sb2Y/9eu+0cyuLdp+jZm9UtSWD1fxOr9pZtvNbMOkx79iZmdX2r9ak763eovauN7Mhs3soyX2eYf/Wn/p1/LD/uNTfW+d7f+sbTCz28ws4z/+R/62T5nZo2Z2ShVtXm7ee9zz5r3nzfEf/4iZXRdWbYKqtpZm9mnz3qedmS2e4nhB38/q+neAf///8b9HNkz6/in5f17ieImvWSScc7F+SfqPkq71b/+2pJ9JSvtfayX1lNjnU5K+5t++VNIdRc8NBTz/VMf6R0lnxl2jCjU7TtKx/u1lkrZKWujfn1+0zw2SPlfiWO2SXvT/zfm3cxXO3yXpZEnfknTxpOdmTc0C1Onj/mtJ+fePKHGsqfa/dXIdKrSrbM0lfUDSN6KshX//g5J+X9K9k7Yr+VoktengnMmTJT07xbm6JX27+GdR0kJJz0h6R3GNJS2V9F7/9jxJz0k63r+/RtKfB3ydvyvpvZI2THr8aEn3R1XPSf+3uyS1lnjuZkmf9G8fL2nzVN9b8v7A3SLpOP+56yV9wr/920XfM78n6bEq2nynpEv9218raotJ+mWpNs/EV7W1lHSqvPeezZIWlzlWLe9n9f474H+T9ICkjKS5ktbJf+8v93/eiDWL4iv2HihJfyTpbv+2k9QsaY6kJklZSdtK7HOhpNv82/8s6YNmh/dUVWmqY/2L377ZZqJmzrnnnHPP+7dflbRd0hL//huS18MiqUVefSc7T9IDzrldzrnd8n4Qz5/q5M65zc65pySNl3j6XzR7alZVnSR9UtL1zrlx//ntkw9UYf+gpqr5v0s6p9DTEKLinzM55x6UtK/anZ1zQ85/d5T3Jl3y0yf+X8R/K+n/mvTUH0r6vnPuN/7xtvv/bnXOPeHf3idpk6Sjqm1XiXY+LO+X7uTHX5a0yMyOrPXYkxxSzyIXS/qRc+7NUs2TNN+/vUDSq37byn1vLZJ0wDn3nL/PA5L+wN/uUf97R5J+Lqlzqsb67wFny3uPk7z3vI/6x3KS+iV9ZKpjRKiqWjrnfumc21zhWIHfz1TnvwPkhfGHnHOjzrn9kp6UdP5U/+eTNErNQhdrgPK7E99Z+KFwzq2V9FN5f4FtlXSfc25TiV2PkveXmZxzo5L2ynuzkaRm84YYfl6qGz3gsdZJOiv4K4vO5JpNeu50eeHz10WP/aOk1yS9W9L/KHHIidfvG9Q0foFpltQsYJ3eJWmV/33zI6swhFaqzpK+5A+n3GhmTRWaV7bmfoh7QVLFIZlqTVWLMkq+FjO7yMyelfSvkq4us++nJd3jnNs66fHjJOXMrN/MBszsihLt7JLXy/BY8fH8tnzTzHJVtr+cJySdOc1jVKrnpZK+U2bXNZL+2MwGJf1Q0mdKHLv4e2unpKyZFVaHvlhSvsRxPyHpRxWavUjSHv89Tjr85zyWn9tp1LKcWt7P6v13wJOSfs/MWv2hzV553yeV/s8LEl+zqMTdA7VY0p7CHTM7RtJ75P01dZSks83sd0vsV6q3qfAX8Tuctxz9H0r6OzN7V4U2THWs7fK61GeTQ2pWYGZL5Q2bfLzQkyJJzrmPy3sNmyStmryfpn79tZgtNQtSpyZJw/73zTckfbPcQcvs/xfyAupp8rrBP1uhbZVqHnYNS9aijLKvxTl3l3Pu3fL+iv3i5B3NbJmkS1Q6qGckrZQ33HCepM+b2XFF+7ZJ+p6k/1ToOZX0/8kLtyvk/UH136t8DeWEVdepvrdOknRfmf0uk3Src65T0oclfdvMUpP2n/je8nuGLpV0o5k9Lq/HcLT4gGbWKy9AzbbvuWrVWstyank/q+vfAc65++UF8kflBc618r5Pqq1FI9QsEnEHqLfkDdkVXCTp5/5wwZC8v6reX2K/Qfl/iflDHQvkd9v7XeByzr0or1v61AptKHssv21vBX1REZtcM5nZfHm9An/lnPv55B2cc2OS7pDf/T/JxOv3dcofWqjRbKlZkDoNyvvlLUl3yZvjc5hy+/vDUM45d0De+P/pFdpWqeZh1/CwWpRTzWvxh8neVWIi76mSjpH0gpltltRqZi/4zw1K+rFzbr9zbqekh+X3splZVl79b3fOfb/oPNucc2N+UP1GqbYEFFZdy9XzY5Lucs6NlNnvE/LmpBR625vl/TKc6ntrrXPuLOfc6fJq9nzhOTM7WdI/SLrQOfd6hTbvlLSwaGg46u+5atVay3JqeT+r+98BzrkvOedWOOc+JC/cPK/K/+cFjVCzSMQaoPzx1rSZFb4ZfiPpA2aW8d9UPyCv52SyeyQVPilwsaSfOOecmeUKQw7+m/uZ8iauysz+2swuqvZY/v3jJG0osU9sJtfM7869S9K3nHPfLWxnnmMKt+VNGH62xCHvk3SuX7ucpHP9x6aq2VRmRc2qrZPvX+TNFZC877nnJj0/5f7+X8uFOn9U/us3s9PN7Fslmle25r7jJG2s+sVWUOLnrKwpXssxhTkOZvZeecNMh/zSds79q3PuSOdcl3OuS9Kbzrlj/KfvlnSW/7PdKul9kjb5x7xF0ibn3A2l2uK7qKgtR5nZg0Fq4Avle3OKel6mqYecfiNv8r7M7D3yftHsqPC9dYT/b5O8Xqav+fffIen7ki4vmiNV2OdBMztkCMZ/T/upvPc4yXvPK553FMvP7TRqWU4t72f1/jsgbWaL/Nsny/sD8P4q/s8LEl+zyLj4P01wi6Rz/NtpSV+XF5qekXRD0XbXS7rAv90s6bvy5oo8Lm88WPI+mfK0vDHhp+V/YsV/7l5JZ5Q4f8lj+c/9uaTPxF2jCjX7Y0kjktYXfa2QF45/5tdhg6TbdfCTGd2S/qHoeFf7r/8FecMHlWp2mry/QPbL+yW6cTbWrJo6+c8tlPfX/9Pyur9PmVynCvv/pKjO/ySpzX/8YklfL9O2cjXvkPR4lLXw7/+7pB3y/lIclHRehdfyWXmhbr1fo98pOtYPJS0rcc6hSff/i7yf6w3yhuok6Xfkdf0/VVTXD/vPfdtvy1Py3rCXFv2/3FfmdX5H3nDfiP+6Cp9ay8p7X8lEVM8uSa/I/yRn0ePF71vHy/uZfNJ/nedW8b31t367f1Womf/4P0jaXbT9Ov/xlKSXJbWUaPM75b3HvSDvPa+p6Ll7JZ0U989phVr+if9/Oiqvh6Twsznd97N6/x3Q7P9cPSPvAwUrKv2fN2LNIvl/iL0BXrf/t2fgPCXfcCvs87AqfJyTms3ems1UnaY4/99KOjngPn+qouCflFqE/Fo+LT+UBNjnIklfTHo9JZ2ooj88q9ynQ9KDMbaZ9zNqVpdfs+JaeGZ2taTbnDdXZ1YwsyXy1rL4l7jbUgo1q85srNNUzOzj8t4YRytuHPzYdVWLMJnZJfI+qr0nxGMmop5mdpqkEefc+hjbMOtqORvfz4pRs/jNigAFAABQT+L+FB4AAEDdIUABAAAERIACMC126AW811vRxb1DOv7VZva0eSuSbzCzC0M6breZ/X1Ix9pcYl0sAAnGHCgA02JmQ865toD7mLz3n1LXUyzerlPSQ/IuOLzXX7F8iXPupSrPk4liQn6J82yW1O28RUIBNAB6oACEysza/MUcn/B7ji70H+8ys01m9v/Kuy5d3sz+i5n9wu9duq7E4Y6QdwmTIWniosYv+cfrN/86cWa22A8xMrOrzOy7ZvYDSfeb2R1m9uGi9t1qZn9gZj1mdq+ZpfwepIVF27xgZh1mtsTMvue38Rdmdqb//CIzu9/MfmlmX1fpS1sASDACFIDpaikavrtL0rCki5xz75V3YdP/XljFXNJvyVtx+1T/9rHyLtGyQtJKO/zal09K2ibpJTP7RzP7/SrbdIakK51zZ0vqk38dSH/V7w/KW/xT0sQFnO+Wt1aUzOx9kjY757ZJ+qqkG51zp8m7FNI/+Lt9QdIj/uu4R9I7qmwXgITIVN4EAKb0lnNuReGOeZdh+r/9MDQu78LgHf7TL7uD13o71//6pX+/TV6gerhwLOfcmJmdL2/1+w/Ku7DuSufcmgptesA5V7g2148k/b1/OZTzJT3snHvrYKaT5F0r8r/Ku/7fpf59STpH0vFF2843s3mSflfS/+638V/NbHeF9gBIGAIUgLD9kaQlklY650b8obXCtc72F21nkv7aOff1qQ7mvImaj0t63MwekBdy1si7pEehF33ytdT2F+0/bGb9ks6T1xNV6hprayUd4y8E+FFJ/81/PCXvUhaHXBzVD1RMIAUaGEN4AMK2QNJ2Pzz1Sjq6zHb3SbranxheuEhw4eK5D/r3l5l38eKCFfKu9SZJmyWt9G9frKn1Sfq4pLN06IWbJU2EtLsk3SDvwsaFCyXfL+/SMfLbtcK/+bC8oCgz+z1JuQrnB5Aw9EABCNvtkn5gZuvkXej22VIbOefuN7P3SFrr9+gMSfpjM9sp6RhJu+RNIv+KmS2TN7dqh6T/0z/EVyTdaWaXy7sI8lTul/QtSfc4594us80dkn4h6aqix/5E0k1m9pS898uH/fNfJ+k7ZvaEvE8J/qbC+QEkDMsYAJhVzOxESVc75/5z3G0BgHIIUAAAAAExBwoAACAgAhQAAEBABCgAAICACFAAAAABEaAAAAACIkABAAAERIACAAAI6H8B36WTMH/cDT8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#代码编写\n",
    "# 计算不同票价中生存与死亡人数 1表示生存，0表示死亡\n",
    "\n",
    "fare_sur = text.groupby(['Fare'])['Survived'].value_counts().sort_values(ascending=False)\n",
    "fare_sur\n",
    "fig=plt.figure(figsize=(10,9))\n",
    "fare_sur.plot(grid=True)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fare_sur1 = text.groupby(['Fare'])['Survived'].value_counts()\n",
    "fig = plt.figure(figsize=(10, 9))\n",
    "fare_sur1.plot(grid=True)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "scrolled": true
   },
   "source": [
    "#### 2.7.5 任务五：可视化展示泰坦尼克号数据集中不同仓位等级的人生存和死亡人员的分布情况。（用柱状图试试）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Pclass  Survived\n",
       "1       1           136\n",
       "        0            80\n",
       "2       0            97\n",
       "        1            87\n",
       "3       0           372\n",
       "        1           119\n",
       "Name: Survived, dtype: int64"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#代码编写\n",
    "# 1表示生存，0表示死亡\n",
    "p=text.groupby(['Pclass'])['Survived'].value_counts()\n",
    "p\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "【思考】看到这个前面几个数据可视化，说说你的第一感受和你的总结"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Pclass', ylabel='count'>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#思考题回答\n",
    "import seaborn as sns\n",
    "sns.countplot(x=\"Pclass\",hue=\"Survived\",data=text)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.7.6 任务六：可视化展示泰坦尼克号数据集中不同年龄的人生存与死亡人数分布情况。(不限表达方式)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x16cbf8a53d0>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 699.875x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#代码编写\n",
    "facet=sns.FacetGrid(text,hue=\"Survived\",aspect=3)\n",
    "facet.map(sns.kdeplot,'Age',shade=True)\n",
    "facet.set(xlim=(0,text['Age'].max()))\n",
    "facet.add_legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.7.7 任务七：可视化展示泰坦尼克号数据集中不同仓位等级的人年龄分布情况。（用折线图试试）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x16cc0af2af0>"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#代码编写\n",
    "\n",
    "text.Age[text.Pclass==1].plot(kind='kde')\n",
    "text.Age[text.Pclass == 2].plot(kind='kde')\n",
    "text.Age[text.Pclass == 3].plot(kind='kde')\n",
    "plt.xlabel(\"age\")\n",
    "plt.legend((1,2,3),loc=\"best\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "【思考】上面所有可视化的例子做一个总体的分析，你看看你能不能有自己发现"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#思考题回答\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "【总结】到这里，我们的可视化就告一段落啦，如果你对数据可视化极其感兴趣，你还可以了解一下其他可视化模块，如：pyecharts，bokeh等。\n",
    "\n",
    "如果你在工作中使用数据可视化，你必须知道数据可视化最大的作用不是炫酷，而是最快最直观的理解数据要表达什么，你觉得呢？"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
